Read the full story here.
Google DeepMind has launched a watermarking tool for AI-generated images
Google DeepMind has launched a new watermarking tool that labels whether images have been generated with AI. The tool, called SynthID, will initially be available only to users of Google’s AI image generator Imagen. Users will be able to generate images and then choose whether to add a watermark or not. The hope is that it could help people tell when AI-generated content is being passed off as real, or protect copyright.
Baby steps: Google DeepMind is now the first Big Tech company to publicly launch such a tool, following a voluntary pledge with the White House to develop responsible AI. Watermarking—a technique where you hide a signal in a piece of text or an image to identify it as AI-generated—has become one of the most popular ideas proposed to curb such harms. It’s a good start, but watermarks alone won’t create more trust online. Read more from me here.
Bits and Bytes
Chinese ChatGPT alternatives just got approved for the general public
Baidu, one of China’s leading artificial-intelligence companies, has announced it will open up access to its ChatGPT-like large language model, Ernie Bot, to the general public. Our reporter Zeyi Yang looks at what this means for Chinese internet users. (MIT Technology Review)
Brain implants helped create a digital avatar of a stroke survivor’s face
Incredible news. Two papers in Nature show major advancements in the effort to translate brain activity into speech. Researchers managed to help women who had lost their ability to speak communicate again with the help of a brain implant, AI algorithms and digital avatars. (MIT Technology Review)
Inside the AI porn marketplace where everything and everyone is for sale
This was an excellent investigation looking at how the generative AI boom has created a seedy marketplace for deepfake porn. Completely predictable and frustrating how little we have done to prevent real-life harms like nonconsensual deepfake pornogrpahy. (404 Media)
An army of overseas workers in “digital sweatshops” power the AI boom
Millions of people working in the Philippines work as data annotators for data company Scale AI. But as this investigation into the questionable labor conditions shows, many workers are earning below the minimum wage and have had payments delayed, reduced, or canceled.
(The Washington Post)
The tropical Island with the hot domain name
Lol. The AI boom has meant Anguilla has hit the jackpot with its .ai domain name. The country is expected to make millions this year from companies wanting the buzzy designation. (Bloomberg)
P.S. We’re hiring!
MIT Technology Review is looking for an ambitious AI reporter to join our team with an emphasis on the intersection of hardware and AI. This position is based in Cambridge, Massachusetts. Sounds like you, or someone you know? Read more here.
These robots know when to ask for help
A new training model, dubbed “KnowNo,” aims to address this problem by teaching robots to ask for our help when orders are unclear. At the same time, it ensures they seek clarification only when necessary, minimizing needless back-and-forth. The result is a smart assistant that tries to make sure it understands what you want without bothering you too much.
Andy Zeng, a research scientist at Google DeepMind who helped develop the new technique, says that while robots can be powerful in many specific scenarios, they are often bad at generalized tasks that require common sense.
For example, when asked to bring you a Coke, the robot needs to first understand that it needs to go into the kitchen, look for the refrigerator, and open the fridge door. Conventionally, these smaller substeps had to be manually programmed, because otherwise the robot would not know that people usually keep their drinks in the kitchen.
That’s something large language models (LLMs) could help to fix, because they have a lot of common-sense knowledge baked in, says Zeng.
Now when the robot is asked to bring a Coke, an LLM, which has a generalized understanding of the world, can generate a step-by-step guide for the robot to follow.
The problem with LLMs, though, is that there’s no way to guarantee that their instructions are possible for the robot to execute. Maybe the person doesn’t have a refrigerator in the kitchen, or the fridge door handle is broken. In these situations, robots need to ask humans for help.
KnowNo makes that possible by combining large language models with statistical tools that quantify confidence levels.
When given an ambiguous instruction like “Put the bowl in the microwave,” KnowNo first generates multiple possible next actions using the language model. Then it creates a confidence score predicting the likelihood that each potential choice is the best one.
The Download: inside the first CRISPR treatment, and smarter robots
The news: A new robot training model, dubbed “KnowNo,” aims to teach robots to ask for our help when orders are unclear. At the same time, it ensures they seek clarification only when necessary, minimizing needless back-and-forth. The result is a smart assistant that tries to make sure it understands what you want without bothering you too much.
Why it matters: While robots can be powerful in many specific scenarios, they are often bad at generalized tasks that require common sense. That’s something large language models could help to fix, because they have a lot of common-sense knowledge baked in. Read the full story.
Medical microrobots that travel inside the body are (still) on their way
The human body is a labyrinth of vessels and tubing, full of barriers that are difficult to break through. That poses a serious hurdle for doctors. Illness is often caused by problems that are hard to visualize and difficult to access. But imagine if we could deploy armies of tiny robots into the body to do the job for us. They could break up hard-to-reach clots, deliver drugs to even the most inaccessible tumors, and even help guide embryos toward implantation.
We’ve been hearing about the use of tiny robots in medicine for years, maybe even decades. And they’re still not here. But experts are adamant that medical microbots are finally coming, and that they could be a game changer for a number of serious diseases. Read the full story.
5 things we didn’t put on our 2024 list of 10 Breakthrough Technologies
We haven’t always been right (RIP, Baxter), but we’ve often been early to spot important areas of progress (we put natural-language processing on our very first list in 2001; today this technology underpins large language models and generative AI tools like ChatGPT).
Every year, our reporters and editors nominate technologies that they think deserve a spot, and we spend weeks debating which ones should make the cut. Here are some of the technologies we didn’t pick this time—and why we’ve left them off, for now.
New drugs for Alzheimer’s disease
Alzmeiher’s patients have long lacked treatment options. Several new drugs have now been proved to slow cognitive decline, albeit modestly, by clearing out harmful plaques in the brain. In July, the FDA approved Leqembi by Eisai and Biogen, and Eli Lilly’s donanemab could soon be next. But the drugs come with serious side effects, including brain swelling and bleeding, which can be fatal in some cases. Plus, they’re hard to administer—patients receive doses via an IV and must receive regular MRIs to check for brain swelling. These drawbacks gave us pause.
Sustainable aviation fuel
Alternative jet fuels made from cooking oil, leftover animal fats, or agricultural waste could reduce emissions from flying. They have been in development for years, and scientists are making steady progress, with several recent demonstration flights. But production and use will need to ramp up significantly for these fuels to make a meaningful climate impact. While they do look promising, there wasn’t a key moment or “breakthrough” that merited a spot for sustainable aviation fuels on this year’s list.
One way to counteract global warming could be to release particles into the stratosphere that reflect the sun’s energy and cool the planet. That idea is highly controversial within the scientific community, but a few researchers and companies have begun exploring whether it’s possible by launching a series of small-scale high-flying tests. One such launch prompted Mexico to ban solar geoengineering experiments earlier this year. It’s not really clear where geoengineering will go from here or whether these early efforts will stall out. Amid that uncertainty, we decided to hold off for now.